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            <article class="content wrap" id="_content" data-uid="TensorFlow.QueueBase">
  
  
  <h1 id="TensorFlow_QueueBase" data-uid="TensorFlow.QueueBase">Class QueueBase
  </h1>
  <div class="markdown level0 summary"><p>Base class for queue implementations.
            Port of Python implementation <a href="https://github.com/tensorflow/tensorflow/blob/r1.3/tensorflow/python/ops/data_flow_ops.py">https://github.com/tensorflow/tensorflow/blob/r1.3/tensorflow/python/ops/data_flow_ops.py</a></p>
</div>
  <div class="markdown level0 conceptual"></div>
  <div class="inheritance">
    <h5>Inheritance</h5>
    <div class="level0"><span class="xref">System.Object</span></div>
    <div class="level1"><span class="xref">QueueBase</span></div>
  </div>
      <div class="level2"><a class="xref" href="TensorFlow.PaddingFIFOQueue.html">PaddingFIFOQueue</a></div>
  <h6><strong>Namespace</strong>: <a class="xref" href="../TensorFlow.html">TensorFlow</a></h6>
  <h6><strong>Assembly</strong>: TensorFlowSharp.dll</h6>
  <h5 id="TensorFlow_QueueBase_syntax">Syntax</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public abstract class QueueBase</code></pre>
  </div>
  <h3 id="constructors">Constructors
  </h3>
  
  
  <a id="TensorFlow_QueueBase__ctor_" data-uid="TensorFlow.QueueBase.#ctor*"></a>
  <h4 id="TensorFlow_QueueBase__ctor_TensorFlow_TFSession_" data-uid="TensorFlow.QueueBase.#ctor(TensorFlow.TFSession)">QueueBase(TFSession)</h4>
  <div class="markdown level1 summary"><p>A queue is a TensorFlow data structure that stores tensors across
            multiple steps, and exposes operations that enqueue and dequeue
            tensors.
            Each queue element is a tuple of one or more tensors, where each
            tuple component has a static dtype, and may have a static shape.The
            queue implementations support versions of enqueue and dequeue that
            handle single elements, versions that support enqueuing and
            dequeuing a batch of elements at once.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public QueueBase (TensorFlow.TFSession session);</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFSession.html">TFSession</a></td>
        <td><span class="parametername">session</span></td>
        <td><p>Session instance</p>
</td>
      </tr>
    </tbody>
  </table>
  <h3 id="properties">Properties
  </h3>
  
  
  <a id="TensorFlow_QueueBase_Session_" data-uid="TensorFlow.QueueBase.Session*"></a>
  <h4 id="TensorFlow_QueueBase_Session" data-uid="TensorFlow.QueueBase.Session">Session</h4>
  <div class="markdown level1 summary"><p>The session that this QueueBased was created for.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">protected TensorFlow.TFSession Session { get; }</code></pre>
  </div>
  <h5 class="propertyValue">Property Value</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFSession.html">TFSession</a></td>
        <td><p>The session.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h3 id="methods">Methods
  </h3>
  
  
  <a id="TensorFlow_QueueBase_Dequeue_" data-uid="TensorFlow.QueueBase.Dequeue*"></a>
  <h4 id="TensorFlow_QueueBase_Dequeue_System_Nullable_System_Int64__System_String_" data-uid="TensorFlow.QueueBase.Dequeue(System.Nullable{System.Int64},System.String)">Dequeue(Nullable&lt;Int64&gt;, String)</h4>
  <div class="markdown level1 summary"><p>Dequeues a tuple of one or more tensors from this queue.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public abstract TensorFlow.TFOutput[] Dequeue (Nullable&lt;long&gt; timeout_ms = null, string operationName = null);</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Nullable</span>&lt;<span class="xref">System.Int64</span>&gt;</td>
        <td><span class="parametername">timeout_ms</span></td>
        <td><p>Optional argument
              If the queue is empty, this operation will block for up to
              timeout_ms milliseconds.
              Note: This option is not supported yet.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">operationName</span></td>
        <td><p>If specified, the created operation in the graph will be this one, otherwise it will be named &#39;QueueDequeueV2&#39;.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFOutput.html">TFOutput</a>[]</td>
        <td><p>One or more tensors that were dequeued as a tuple.
              The TFOperation can be fetched from the resulting TFOutput, by fethching the Operation property from the result.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 id="TensorFlow_QueueBase_Dequeue_System_Nullable_System_Int64__System_String__remarks">Remarks</h5>
  <div class="markdown level1 remarks"><p>This operation has k outputs, where k is the number of components
              in the tuples stored in the given queue, and output i is the ith
              component of the dequeued tuple.</p>
</div>
  
  
  <a id="TensorFlow_QueueBase_Enqueue_" data-uid="TensorFlow.QueueBase.Enqueue*"></a>
  <h4 id="TensorFlow_QueueBase_Enqueue_TensorFlow_TFOutput___System_Nullable_System_Int64__System_String_" data-uid="TensorFlow.QueueBase.Enqueue(TensorFlow.TFOutput[],System.Nullable{System.Int64},System.String)">Enqueue(TFOutput[], Nullable&lt;Int64&gt;, String)</h4>
  <div class="markdown level1 summary"><p>Enqueues a tuple of one or more tensors in this queue.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public abstract TensorFlow.TFOperation Enqueue (TensorFlow.TFOutput[] components, Nullable&lt;long&gt; timeout_ms = null, string operationName = null);</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFOutput.html">TFOutput</a>[]</td>
        <td><span class="parametername">components</span></td>
        <td><p>One or more tensors from which the enqueued tensors should be taken.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.Nullable</span>&lt;<span class="xref">System.Int64</span>&gt;</td>
        <td><span class="parametername">timeout_ms</span></td>
        <td><p>Optional argument
              If the queue is full, this operation will block for up to
              timeout_ms milliseconds.
              Note: This option is not supported yet.</p>
</td>
      </tr>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">operationName</span></td>
        <td><p>If specified, the created operation in the graph will be this one, otherwise it will be named &#39;QueueEnqueueV2&#39;.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFOperation.html">TFOperation</a></td>
        <td><p>Returns the description of the operation</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 id="TensorFlow_QueueBase_Enqueue_TensorFlow_TFOutput___System_Nullable_System_Int64__System_String__remarks">Remarks</h5>
  <div class="markdown level1 remarks"><p>The components input has k elements, which correspond to the components of
              tuples stored in the given queue.</p>
</div>
  
  
  <a id="TensorFlow_QueueBase_GetSize_" data-uid="TensorFlow.QueueBase.GetSize*"></a>
  <h4 id="TensorFlow_QueueBase_GetSize_System_String_" data-uid="TensorFlow.QueueBase.GetSize(System.String)">GetSize(String)</h4>
  <div class="markdown level1 summary"><p>Gets the size of this queue.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public abstract TensorFlow.TFOutput GetSize (string operationName = null);</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><span class="parametername">operationName</span></td>
        <td><p>To be added.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFOutput.html">TFOutput</a></td>
        <td><p>queue size</p>
</td>
      </tr>
    </tbody>
  </table>
</article>
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